Sunday, June 28, 2015

Will paying for internet content raise productivity growth?

Productivity growth is important because the opportunities
available to our children and grandchildren depend on it. As I write that I can
almost hear some people saying: “Oh yeah, who needs more stuff?” It would be
great if people who are satisfied with their current living standards didn’t
have to worry about productivity growth. Unfortunately, even those people need
productivity growth because their governments have already spent some of their
future income on their behalf. Material living standards will depend on the
income that remains after governments have taken away a slice (via reduced
welfare payments and services or higher taxes) in order to service the public debts
that continue to accumulate.

Some economists are worrying that the rate of productivity
growth in high-income countries has declined since the turn of the century and
is hampering recovery from the great recession in Europe and North America. In
an article published by the Australian Treasury in 2013, Christine Carmody suggested
that the substantial decline in productivity growth that has occurred in Australia
might be related to a more general decline in productivity growth in other high-income
countries. However, when I went looking for more recent OECD data on productivity to illustrate the slowdown I started to doubt whether it is a
general phenomenon. The Figure below shows that in only about half of the
countries covered by the OECD data was the rate of multifactor productivity (MFP)
growth during the 2001 to 2007 lower than that in 1995 to 2001.

(Please click on graph for a better view.)

Multifactor productivity (MFP) measures the growth in value
added output per unit of labour and capital input used. Labour productivity is
sometimes still used in such comparisons but if we are interested in productive
efficiency it makes sense to remove the impact of capital deepening (i.e.
increasing capital per unit of labour).

After I saw the ambiguous OECD data I decided to take
another look at Tyler Cowen’s book, The Great Stagnation, because that was where I had first come across the idea
that all the low hanging fruit has been picked. As it happens Tyler’s book was
about America and he did not rely on national productivity data to make his
point. In fact he was highly critical of national productivity data. (Tyler
relied heavily on data on median family incomes, which have growth slowly since
the mid-1970s. Some analysis by Scott Winship suggests to me that there may
also be problems in using that data to measure trends in productivity and
earnings.)

Robert Gordon’s view that there has been a secular decline
in productivity growth that is likely to continue is based on an examination of
longer term trends in productivity growth in the United States. He notes that
in the eight decades before 1972 labour productivity growth in the U.S grew 0.8
percent per year faster than in the four decades since then. He is sceptical of
claims by techno-optimists such as Erik Brynjolfsson and Andrew McAfee that the
global economy is on the cusp of a dramatic growth spurt driven by smart
machines taking advantage of advances in computer processing, artificial
intelligence, networked communication etc.

Tyler Cowen seems to be in broad
agreement with what Bob Gordon writes about the past, but tends to agree with
the techno-optimists about productivity growth in the future. There are other
important contributors to this debate, including Joel Mokyr who makes the point
that that the indirect effects of science on productivity through the tools it
provides scientific research – such as searchable databanks, quantum chemistry
simulation and highly complex statistical analysis - may, in the long run,
dwarf the direct effects. The views of various contributors to the discussion
have been summarised by Andrew Flowers in EconSouth.

In a recent article in the New York Times Paul Krugman made
a useful contribution by suggesting that the productivity numbers are missing
the benefits of new products and services. He wrote: “I get a lot of pleasure
from technology that lets me watch streamed performances by my favourite
musicians, but that doesn’t get counted in GDP”.

That point is, of course, not new. Australia’s Productivity Commission
(with which I am still proud to claim past links) has recognized the problem of
measuring the outputs of the information and communications technologies (ICT) industries
- for example, see the staff paper on productivity concepts and measurement by Jenny
Gordon, Shiji Zhao, Paul Gretton. The problems of measuring productivity of the
internet were discussed at some length by Tyler Cowen in Chapter 3 of The Great Stagnation.

In order to answer the question I posed above I had hoped to point to some concrete evidence
that content providers are finding effective ways to charge the users of their
products. It seems all too obvious that it is happening with respect to a great deal of
music, video and news, but I have not been able to find a summary of relevant
information on the extent to which this is happening. Information such as that is usually easy to find on the Internet, but when I type in the words ‘revenue’, ‘internet’ and ‘content’ into
search engines what comes up is a lot of information on models that firms can use to
charge for content. Perhaps that is a sign of the times! The success of
major sporting organisations in obtaining revenue from the entertainment they
provide via all communications media seems to point toward a future in which consumers
will pay for content directly and/or expose themselves to greater, and more personalised,
advertising.

As people have to pay for more internet content it seems
likely that will,of itself, make the productivity numbers for ICT industries
look better, even though underlying productivity will not have improved and
well-being of consumers may have declined. The potential upside of this return
to old style capitalism is that as people pay for content there will be an increased
incentive for firms to invest in providing content and to employ more people to
produce content.

Postscript 1:

Jim Belshaw has
some related comments on his blog raising some questions about education, on-the-job learning and retention of corporate knowledge. My discussion with Jim in the comments
section below has introduced me to the concept of productisation, which
involves combining suitable elements to form something that is standardized,
repeatable and comprehendible as product (a longer definition is provided in this abstract). It has also prompted me
to think more about the implications for productivity of ICT investment at the
firm level.

The Productivity
Commission’s research report "ICT Use and Productivity: A Synthesis from
Studies of Australian Firms" published over a decade ago indicates that the rate
of ICT uptake and effects on performance differ substantially across firms,
even in similar circumstances. The differences were attributed to: differing technology
and innovation strategies; availability of complementary skills; and
differences in capacity to ‘learn-by-doing’. The Commission also suggests that differences
between firms in their accumulation of organisational capital sets them apart
from each other in their effective use of technology and in related
innovation.

A report by Ben
Miller and Robert Atkinson entitled “Raising European Productivity Growth
Through ICT” (prepared for the Information Technology and Innovation
Foundation and published in June 2014) also draws heavily on firm-level
productivity studies. The report cites many recent studies suggesting that
investment in ICT has continued to have a strongly positive impact on
productivity at firm level. The report argues that the regulatory environment
in Europe has hindered the ICT investment needed to close Europe's increasing
productivity gap with America. Postscript 2:Noric Dilanchian has drawn my attention to a post by Timothy Taylor, the Conversable Economist, on a new OECD report entitled "The Future of Productivity". The OECD report seems to cover some similar ground to the report by Ben Miller and Robert Atkinson referred to above. I will read it properly and write more about it later.

15 comments:

I thought that this was another very interesting post, Winton. An initial question to you. Does multi-factor productivity accurately measure productivity improvement in the services sector? I ask this because it seems to me that the biggest productivity improvements in services comes from the investment of labour, not physical capital.

Thanks Jim. There are some major problems in measuring MFP in services. One is the problem of measuring output in the government sector where there is often no market price for services provided. There is also the more general problem that quality change is probably not adequately accounted for in price indexes used to deflate values in order to measure change in volume of outputs and inputs.

I am not sure to what extent productivity improvements in services are embodied in labour (skills) rather than capital equipment (e.g.new medical technology). For example, surgeons acquire new skills to use new technology. Perhaps the skills of surgeons are reflected in their pay. The measurement of the contribution of the new equipment is even more problematic given that the price may reflect the ability a technology developer to recoup development costs. The new technology may also render old technology obsolete, so there is also the question of how well that is reflected in depreciation assumptions. The output of surgeons that we should be measuring is improvement in longevity and quality of life of patients, but I doubt whether that is actually measured in the national MFP numbers.

Credentialism is another complicating factor. When governments regulate to require people selling services to have minimum qualifications, that may raise measured inputs more than justified by improvement in the quality of the inputs. Childcare is an example that comes to mind, but I am not sure that it is a good example. In this instance credentials might provide unmeasured outputs in the form of early childhood education.

I first really focused on this one back in the 1980s centered on what was called productisation, sometimes also linked to industrialisation of services. Central to this was the analysis of services and processes to break them into component parts for subsequent re-use. The major investment input was time, although it was facilitated by the growing availability of computer equipment.

Something similar happened with the fall in staff numbers in telecoms or power. Central to this was doing things better rather than physical capital investment. Again, time investment was required.

Now we have all the content creation industries where similar issues apply.

The normal definition of capital investment does not accurately reflect this shift in investment from physical capital. I assume that this affects productivity measurement plus analysis based on that measurement.

Hi JimI could not remember productisation, so I had to look it up. The word is almost as ugly as incentivation, but the concepts involved are certainly relevant to productivity measurement issues.

Going back to your original question I went looking for a discussion of problems in MFP measurement by the ABS. The paper I found is interesting but it doesn't seem to get to grips with measurement problems arising from quality changes that are not reflected in market prices. If you are interested, it can be downloaded here: http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/1351.0.55.0042005?OpenDocument

I have to say, Winton, that that was an eye-glazing paper although interesting. I terms of my argument, capital was (I think) defined as physical capital, labour measured by labour input in a period.

Central to my thesis is the importance of what we might call intellectual capital. This is often expressed in terms of accumulating investment in R&D or, alternatively, the value of things such as brands or patents. However, there is another component that might also be better called knowledge or, better, improved knowledge. For my purposes, I will define it simply the time invested (the immediate production value foregone) in learning how to do something better or to do something new.

That investment is not directly measurable in current productivity statistics and may indeed not be measurable. In cost terms, it means higher labour costs now. Later, it may mean lower labour costs for a given output, higher output or improved quality or some combination of them all. The way the stats work is the gain is attributed to either labour or physical capital, thus distorting the equation.

JimThe intangibles plus the improved technical knowledge is a large part of what MFP does measure. You will recall that MFP is often referred to as "the residual" or "measure of our ignorance" because it is that part of the growth of production that is not attributable to accumulation of capital or increased labour input. It is sometimes assumed to measure technological change, but it also reflects changes in management efficiency (the old X efficiency concept).

One branch of productivity research involves adjusting the capital and labour input measures to account for quality change and thus attribute as much as possible of the residual to either capital or labour. My understanding is that the ABS (and OECD) don't go far down that path in the MFP measures that they publish.

I'm not sure if that answers your question.

Incidentally, if business makes a lot of use of free stuff that has become available on the internet e.g. Google maps, that would raise measured MFP growth.

Thanks, Winton. That does help clarify my thinking. So, in simple terms, the changing impact of the type of thing that I am talking about would be indirectly measured by changes in the residual.

My interest in these change processes at firm or industry level began when I was in DITAC and then continued through my consulting work. A lot of it peeps through now in my management analysis, some in the policy stuff. Essentially, I take what I see at firm level, generalise, try to test and then discuss implications. In industry economics terms, its not always easy to link changes in conduct, structure and performance derived from observation to some of the economic models or conventional statistical measurements or analysis based on those models or measurements.

Jim,I have been thinking that productivity measurement is an area where economists should be doing a lot more work at a very micro level (firm, factory or even machine) and then building up a picture from there. I guess you would not have too many problems with that idea.

Economists learned about the importance of the residual by attempting to account for national economic growth using conventional models. But when we come to try to think about technological change we have to fall back on micro level analogies. For example, in our more inspired moments we say some advance is like the domestication of the horse to replace human power, or like motorised trucks replacing horse drawn vehicles, or like use of fertilisers in agriculture, or the difference between conventional chess and freestyle chess. This type of thinking is good for developing hypotheses but I have not seen much testing or measurement done to assess what particular innovations are really like. Perhaps I have not been looking in the right places.

I've only scan read this post and the comments. It needs proper reading as I'm unfamiliar with the core and many related economics concepts. I have however tracked discussion of productivity in Australia for decades. This has flowed into observing the rapid development of the BRIC countries and trying to engage with and understand the drivers.

I'm only entering this comment to put forward a footnote. It is the need to have rigour in definitions of terms such as content (industry term), intellectual property (legal term), intellectual capital and intellectual assets (both management terms), and intangible assets (accounting standards term).

From my reading there's been a stagnation of thinking for such definitions over the last 15 years or so. This is strange given the explosion in valuation of some areas of content since about 2006, eg data (as exploited by business models applied by Google, Facebook and others). Perhaps there is literature that passed me by.

All those definitions I presume would shed some light on the points touched on by Winton as regards productivity measurement.

Personally, in legal work yesterday I had to pull up some very experienced people in business who to my mind were drifting all over the place in their use of such terms. They had picked up on a term which was new to me - "informal IP". After research I wrote a piece tearing the term to pieces as having no clear meaning and not even any validity (in that it assumed that patents and trade marks, being registered IP, had qualities worth describing as "formal"; yet this fell into the trap of assuming registration per se adds value).

To end I will in this footnote comment share a historical point that got me here. From the early 1990s Jim Belshaw and I inspired each other to develop a glossary of relevant terms. Developing definitions for this area was always a multidisciplinary exercise. To this day I use that glossary to guide legal work by putting down a strong foundation of definitions used in contracts and advisory work.

Thanks Noric. I can understand why rigour in definitions is particularly important in legal work. I guess that in the nature of what they do senior people in business draw on ideas from law, accounting, management, economics, psychology, engineering etc and have a tendency to drift all over the place.

Regarding my discussion with Jim, after reading your comment it occurred to me that I should check on ABS's treatment of intangible assets in measurement of capital stock. Apparently ABS include three types of intangible assets in capital stock (presumably those for which accounting data are most readily available). I should probably have clarified that sooner.

Winton, just picking up Noric's point a little and linking it to the discussion over at my place, one of the things that we (Noric and I) both noticed a few years back was the apparent change in the delivery of legal services. I had been working as a consultant in the law area and was doing some work with Noric. Part of my role was to look at the business issues and commercial models built into client legal requests to make it easier for Noric to provide the subsequent legal advice. For example, a client would say draft a contract, but for what purpose, what were the commercial issues involved that should be reflected in the legal drafting?

Two things became apparent. On the client side, there had been a decline in the in-house knowledge that would once have informed the request for legal advice. There was also an increase in impatience. Just get us that contract. Talking to in-house counsel, they suffered from the same problem.

On the legal side, there was greater reliance on and availability of templates and precedents. That can be efficient, but what we had was less informed clients being given boiler plate solutions by lawyers who weren't forced to think. The rework that was subsequently required was okay, it added to fees.

In productivity terms, we had an un-measurable reduction in the quality of legal advice. Our experiment, the combination of economic/commercial analysis from an informed legal perspective(me)with the specific legal skills (Noric) didn't work very well because clients saw it as increasing their costs. That wasn't true, but the firm was seen as going outside its ambit.

Part of the driver in my case lay in my experience as a manager and a consultant where I had seen large legal bills flowing from badly designed requests for advice. It's very hard for organisations to monitor this, harder still since their in-house know how declined. In one case (not with Noric), and after $53,000 had been spent, I aborted a whole legal process by simply redefining the question.

From my perspective, it's not easy bridging the gaps between the macro productivity analysis and the conclusions I have drawn at firm level.

JimThis example raises several issues, one of which is touched upon in my next post i.e. the question of the extent to which it makes sense to unbundle services to enable the more routine aspects to be computerised.

Regarding the harvesting of knowledge gained at firm level, I was hoping that McKinsey's new book "No Ordinary Disruption" would be good at that. I was disappointed. I will write more about that later.

Thanks Winton and Jim for both your comments, very precise and useful.

Winton, as regards McKinsey I've found in recent years such a drop in the quality of that firm's published work that I've stopped reading it. That's after more than 17 years of taking McKinsey seriously. The subject matter I was especially keen to know about was IT. McKinsey has just become very out of touch with what goes on in market places for apps, data and mobile-driven changes - all areas that touch on my client work.

From my perspective the question we are asking is about productivity, measuring it, understanding its drivers, and building it. Our comments seem to be mostly about impediments to such tasks for productivity, both of you applying competency and experience that extends to industry and national economics.

My experience is focused at the firm and client-firm transactions level.

So what I observed years ago as a race to the bottom in price terms for legal services, is today from my experience also often a race to the bottom in quality terms. Many factors contribute to this, I'll focus on the change in the platform and the lack of epistomology.

PLATFORM: This race is partly due to new ways of working, for example a change in what I term the "platform for delivery of legal services". Keeping it simple, the platform used to be face to face meetings and workbees, it is now electronic. That changes many things, too many to note here, other to note that it often contributes to the race to the bottom in price and quality terms.

EPISTOMOLOGY: Perhaps more important than the change in the platform is the productivity impediment at the client-firm transactions level arising because the world has changed but perceptions about roles and requirements have barely changed, yet.

My final note on that cycle is that in a world changing faster than any person can understand, let alone keep track of, I find it laughable that there is such silence or discussion of perceptions, ideology, belief systems, mindsets, and epistemology. Hence we are using the same old textbooks, but living in a different universe.

Hi NoricMcKinsey's book is about technological change, globalisation, population ageing and flows of goods, capital, people and information. I written about it in an article that I have scheduled for next Sunday. I bought the book mainly because I thought it might have useful insights about adoption of new technology. What they write makes sense but they didn't offer the practical insights that I was hoping to find.Thanks for your comments about legal services. I will try to keep them in mind in my further work in this area over the next couple of weeks. I am wondering to what extent similar issues might also be arising in relation to other services. It is obvious that new technology often requires work to be re-designed if it is to be used effectively, but the changes required will not be immediately obvious to users and suppliers of services.

Looking at some of the prices charged for legal services at the big end of town, I'm not absolutely convinced about the race to the bottom in price terms although I accept that it happening in some areas.

Electronic communication and especially emails does, I think, make for laziness and haste. It also contributes to the misuse of templates.

Epistemology is a difficult one and one that deserves a really full response at some point. I'm simply not sure. What I have been finding is that language shifts based on underlying but shifting mental models are a real problem. As you know jargon shifts all the time. It's a problem for me in some of my work because I don't accept the underlying models and therefore struggle to express ideas and advice, more correctly squash ideas and advice, into acceptable terms.

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